按字符串长度排序

fruits = ["apple", "banana", "cherry", "date", "elderberry"]
fruits.sort(key=len)
print(fruits)  # 输出: ['date', 'apple', 'banana', 'cherry', 'elderberry']

按自定义函数排序

# 按绝对值排序
numbers = [-5, 3, -2, 8, -1]
numbers.sort(key=abs)
print(numbers)  # 输出: [-1, -2, 3, -5, 8]

# 按字符串的第二个字符排序
words = ["banana", "apple", "cherry", "date"]
sorted_words = sorted(words, key=lambda x: x[1])
print(sorted_words)  # 输出: ['date', 'banana', 'apple', 'cherry']

字典列表排序

students = [
    {"name": "Alice", "age": 20, "grade": 88},
    {"name": "Bob", "age": 22, "grade": 92},
    {"name": "Charlie", "age": 19, "grade": 85}
]

# 按年龄排序
students_sorted_by_age = sorted(students, key=lambda s: s['age'])
print(students_sorted_by_age)
# 输出: [{'name': 'Charlie', 'age': 19, 'grade': 85}, 
#        {'name': 'Alice', 'age': 20, 'grade': 88}, 
#        {'name': 'Bob', 'age': 22, 'grade': 92}]

# 按成绩降序排序
students.sort(key=lambda s: s['grade'], reverse=True)
print(students)
# 输出: [{'name': 'Bob', 'age': 22, 'grade': 92}, 
#        {'name': 'Alice', 'age': 20, 'grade': 88}, 
#        {'name': 'Charlie', 'age': 19, 'grade': 85}]

多级排序

# 先按成绩降序，再按年龄升序
students = [
    {"name": "Alice", "age": 20, "grade": 88},
    {"name": "Bob", "age": 22, "grade": 92},
    {"name": "Charlie", "age": 19, "grade": 88},
    {"name": "David", "age": 21, "grade": 92}
]

students_sorted = sorted(students, key=lambda s: (-s['grade'], s['age']))
for student in students_sorted:
    print(f"{student['name']} - Age: {student['age']}, Grade: {student['grade']}")
    
# 输出:
# Bob - Age: 22, Grade: 92
# David - Age: 21, Grade: 92
# Alice - Age: 20, Grade: 88
# Charlie - Age: 19, Grade: 88

使用operator模块

import operator

# 按字典的值排序
students = [
    {"name": "Alice", "age": 20, "grade": 88},
    {"name": "Bob", "age": 22, "grade": 92},
    {"name": "Charlie", "age": 19, "grade": 85}
]

# 按年龄排序
students.sort(key=operator.itemgetter('age'))
print(students)

# 多级排序：先按成绩，再按年龄
students.sort(key=operator.itemgetter('grade', 'age'))
print(students)

自定义排序类

class Product:
    def __init__(self, name, price, rating):
        self.name = name
        self.price = price
        self.rating = rating
        
    def __repr__(self):
        return f"Product('{self.name}', {self.price}, {self.rating})"

products = [
    Product("Laptop", 1200, 4.5),
    Product("Phone", 800, 4.2),
    Product("Tablet", 600, 4.7),
    Product("Monitor", 300, 4.3)
]

# 按价格排序
products.sort(key=lambda p: p.price)
print(products)

# 按评分降序排序
products.sort(key=lambda p: p.rating, reverse=True)
print(products)

重要注意事项

• Python的排序算法是Timsort，一种混合稳定排序算法
• 时间复杂度：平均和最坏情况均为O(n log n)
• sort()方法会改变原始列表，sorted()函数会返回新列表
• 当对包含不同数据类型的列表排序时，Python 3会抛出TypeError异常
• 使用key参数比cmp参数更高效（Python 3已移除cmp参数）
• 对于稳定性要求高的场景，Python排序是稳定的（相等元素的顺序保持不变）

性能优化建议

• 避免在key函数中进行复杂计算
• 对于大型数据集，考虑使用内置排序而非自定义算法
• 如果只需要部分排序结果，可以使用heapq模块
• 对于已部分排序的数据，Timsort表现尤为高效
• 当排序键计算成本高时，考虑使用Schwartzian变换（装饰-排序-去装饰）